Uncovering novel therapeutic targets in glucose, nucleotides and lipids metabolism during cancer and neurological diseases.

BACKGROUND: Cell metabolism functions without a stop in normal and pathological cells. Different metabolic changes occur in the disease. Cell metabolism influences biochemical and metabolic processes, signaling pathways, and gene regulation. Knowledge regarding disease metabolism is limited. OBJECTIVE: The review examines the cell metabolism of glucose, nucleotides, and lipids during homeostatic and pathological conditions of neurotoxicity, neuroimmunological disease, Parkinson's disease, thymoma in myasthenia gravis, and colorectal cancer. METHODS: Data collection includes electronic databases, the National Center for Biotechnology Information, and Google Scholar, with several inclusion criteria: cell metabolism, glucose metabolism, nucleotide metabolism, and lipid metabolism in health and disease patients suffering from neurotoxicity, neuroinflammation, Parkinson's disease, thymoma in myasthenia gravis. The initial number of collected and analyzed papers is 250. The final analysis included 150 studies out of 94 selected papers. After the selection process, 62.67% remains useful. RESULTS AND CONCLUSION: A literature search shows that signaling molecules are involved in metabolic changes in cells. Differences between cancer and neuroimmunological diseases are present in the result section. Our finding enables insight into novel therapeutic targets and the development of scientific approaches for cancer and neurological disease onset, outcome, progression, and treatment, highlighting the importance of metabolic dysregulation. Current understanding, emerging research technologies and potential therapeutic interventions in metabolic programming is disucussed and highlighted.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy.

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Seleno-amino Acid Metabolism Reshapes the Tumor Microenvironment: from Cytotoxicity to Immunotherapy.

Selenium (Se) is an essential trace element for biological processes. Seleno-amino acids (Se-AAs), known as the organic forms of Se, and their metabolic reprogramming have been increasingly recognized to regulate antioxidant defense, enzyme activity, and tumorigenesis. Therefore, there is emerging interest in exploring the potential application of Se-AAs in antitumor therapy. In addition to playing a vital role in inhibiting tumor growth, accumulating evidence has revealed that Se-AA metabolism could reshape the tumor microenvironment (TME) and enhance immunotherapy responses. This review presents a comprehensive overview of the current progress in multifunctional Se-AAs for antitumor treatment, with a particular emphasis on elucidating the crosstalk between Se-AA metabolism and various cell types in the TME, including tumor cells, T cells, macrophages, and natural killer cells. Furthermore, novel applications integrating Se-AAs are also discussed alongside prospects to provide new insights into this emerging field.

Taste alteration and its relationship with nutritional status among cancer patients receiving chemotherapy, cross-sectional study.

The aim of this study is to determine the prevalence of taste alterations (TAs) during chemotherapy and their association with nutritional status and malnutrition. In addition to the associated factors with TA, including sociodemographic health-related factors and clinical status, and to investigate coping strategies to manage TA. A multicenter cross-sectional design study was conducted on 120 cancer patients aged at least 18 who had been undergoing at least one round of chemotherapy. TAs were evaluated using the chemotherapy-induced taste alteration scale (CiTAS), the malnutrition universal screening tool (MUST) was used for nutritional screening, the antineoplastic side effects scale (ASES) was used for subjective assessment of chemotherapy side effects, and the Charlson comorbidity index (CCI) was used for comorbidity assessment. SPSS21 software was used to analyze the data, and the independent T-test and one-way ANOVA test were used to determine the association between TAs and a variety of related variables. The prevalence of TAs was 98.3%. Among participants, 48.3% were at low risk of malnutrition, 20% at medium risk, and 31.7% at high risk. Malnutrition risk was associated with taste disorders (p<0.05). Patients' age, gender, educational level, and physical status were associated with TAs (p<0.05). Type of cancer, chemotherapy regimen, and number of chemotherapy cycles were also associated with TAs (p<0.05). A variety of antineoplastic side effects were associated with TAs (p<0.05), including nausea, vomiting, dry mouth, sore mouth and throat, excessive thirst, swallowing difficulty, appetite changes, weight loss, dizziness, lack of energy, disturbed sleep, anxiety, and difficulty concentrating. TAs were associated with an increased number of comorbidities, and individuals with diabetes, pulmonary diseases, and hypertension were associated with TAs (P<0.05). Patients in this study rarely practice self-management strategies to cope with TAs. A high prevalence (98.3%) of TAs in cancer patients receiving chemotherapy was found, and it was linked to a variety of negative outcomes. Chemotherapy-induced TAs are an underestimated side effect that requires more attention from patients and health care providers.

Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning.

BACKGROUND: The prediction of drug sensitivity plays a crucial role in improving the therapeutic effect of drugs. However, testing the effectiveness of drugs is challenging due to the complex mechanism of drug reactions and the lack of interpretability in most machine learning and deep learning methods. Therefore, it is imperative to establish an interpretable model that receives various cell line and drug feature data to learn drug response mechanisms and achieve stable predictions between available datasets. RESULTS: This study proposes a new and interpretable deep learning model, DrugGene, which integrates gene expression, gene mutation, gene copy number variation of cancer cells, and chemical characteristics of anticancer drugs to predict their sensitivity. This model comprises two different branches of neural networks, where the first involves a hierarchical structure of biological subsystems that uses the biological processes of human cells to form a visual neural network (VNN) and an interpretable deep neural network for human cancer cells. DrugGene receives genotype input from the cell line and detects changes in the subsystem states. We also employ a traditional artificial neural network (ANN) to capture the chemical structural features of drugs. DrugGene generates final drug response predictions by combining VNN and ANN and integrating their outputs into a fully connected layer. The experimental results using drug sensitivity data extracted from the Cancer Drug Sensitivity Genome Database and the Cancer Treatment Response Portal v2 reveal that the proposed model is better than existing prediction methods. Therefore, our model achieves higher accuracy, learns the reaction mechanisms between anticancer drugs and cell lines from various features, and interprets the model's predicted results. CONCLUSIONS: Our method utilizes biological pathways to construct neural networks, which can use genotypes to monitor changes in the state of network subsystems, thereby interpreting the prediction results in the model and achieving satisfactory prediction accuracy. This will help explore new directions in cancer treatment. More available code resources can be downloaded for free from GitHub ( https://github.com/pangweixiong/DrugGene ).

Pragmatic nationwide master observational trial based on genomic alterations in advanced solid tumors: KOrean Precision Medicine Networking Group Study of MOlecular profiling guided therapy based on genomic alterations in advanced Solid tumors (KOSMOS)-II study protocol KCSG AL-22-09.

BACKGROUND: Next-generation sequencing (NGS) has been introduced to many Korean institutions to support molecular diagnostics in cancer since 2017, when it became eligible for reimbursement by the National Health Insurance Service. However, the uptake of molecularly guided treatment (MGT) based on NGS results has been limited because of stringent regulations regarding prescriptions outside of approved indications, a lack of clinical trial opportunities, and limited access to molecular tumor boards (MTB) at most institutions. The KOSMOS-II study was designed to demonstrate the feasibility and effectiveness of MGT, informed by MTBs, using a nationwide precision medicine platform. METHODS: The KOSMOS-II trial is a large-scale nationwide master observational study. It involves a framework for screening patients with metastatic solid tumors for actionable genetic alterations based on local NGS testing. It recommends MGT through a remote and centralized MTB meeting held biweekly. MGT can include one of the following options: Tier 1, the therapeutic use of investigational drugs targeting genetic alterations such as ALK, EGFR, ERBB2, BRAF, FH, ROS1, and RET, or those with high tumor mutational burden; Tier 2, comprising drugs with approved indications or those permitted for treatment outside of the indications approved by the Health Insurance Review and Assessment Service of Korea; Tier 3, involving clinical trials matching the genetic alterations recommended by the MTB. Given the anticipated proportion of patients receiving MGT in the range of 50% ± 3.25%, this study aims to enroll 1,000 patients. Patients must have progressed to one or more lines of therapy and undergone NGS before enrollment. DISCUSSION: This pragmatic master protocol provides a mass-screening platform for rare genetic alterations and high-quality real-world data. Collateral clinical trials, translational studies, and clinico-genomic databases will contribute to generating evidence for drug repositioning and the development of new biomarkers. TRIAL REGISTRATION: NCT05525858.

Contrastive learning for enhancing feature extraction in anticancer peptides.

Cancer, recognized as a primary cause of death worldwide, has profound health implications and incurs a substantial social burden. Numerous efforts have been made to develop cancer treatments, among which anticancer peptides (ACPs) are garnering recognition for their potential applications. While ACP screening is time-consuming and costly, in silico prediction tools provide a way to overcome these challenges. Herein, we present a deep learning model designed to screen ACPs using peptide sequences only. A contrastive learning technique was applied to enhance model performance, yielding better results than a model trained solely on binary classification loss. Furthermore, two independent encoders were employed as a replacement for data augmentation, a technique commonly used in contrastive learning. Our model achieved superior performance on five of six benchmark datasets against previous state-of-the-art models. As prediction tools advance, the potential in peptide-based cancer therapeutics increases, promising a brighter future for oncology research and patient care.

Small-Molecule Inhibitors of TIPE3 Protein Identified through Deep Learning Suppress Cancer Cell Growth In Vitro.

Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human cancers and has been established to significantly promote tumor cell proliferation, migration, and invasion and inhibit the apoptosis of cancer cells. Thus, inhibiting the function of TIPE3 is expected to be an effective strategy against cancer. The advancement of artificial intelligence (AI)-driven drug development has recently invigorated research in anti-cancer drug development. In this work, we incorporated DFCNN, Autodock Vina docking, DeepBindBC, MD, and metadynamics to efficiently identify inhibitors of TIPE3 from a ZINC compound dataset. Six potential candidates were selected for further experimental study to validate their anti-tumor activity. Among these, three small-molecule compounds (K784-8160, E745-0011, and 7238-1516) showed significant anti-tumor activity in vitro, leading to reduced tumor cell viability, proliferation, and migration and enhanced apoptotic tumor cell death. Notably, E745-0011 and 7238-1516 exhibited selective cytotoxicity toward tumor cells with high TIPE3 expression while having little or no effect on normal human cells or tumor cells with low TIPE3 expression. A molecular docking analysis further supported their interactions with TIPE3, highlighting hydrophobic interactions and their shared interaction residues and offering insights for designing more effective inhibitors. Taken together, this work demonstrates the feasibility of incorporating deep learning and MD simulations in virtual drug screening and provides inhibitors with significant potential for anti-cancer drug development against TIPE3-.

Applications of Pyrrole and Pyridine-based Heterocycles in Cancer Diagnosis and Treatment.

BACKGROUND: The escalation of cancer worldwide is one of the major causes of economy burden and loss of human resources. According to the American Cancer Society, there will be 1,958,310 new cancer cases and 609,820 projected cancer deaths in 2023 in the United States. It is projected that by 2040, the burden of global cancer is expected to rise to 29.5 million per year, causing a death toll of 16.4 million. The hemostasis regulation by cellular protein synthesis and their targeted degradation is required for normal cell growth. The imbalance in hemostasis causes unbridled growth in cells and results in cancer. The DNA of cells needs to be targeted by chemotherapeutic agents for cancer treatment, but at the same time, their efficacy and toxicity also need to be considered for successful treatment. OBJECTIVE: The objective of this study is to review the published work on pyrrole and pyridine, which have been prominent in the diagnosis and possess anticancer activity, to obtain some novel lead molecules of improved cancer therapeutic. METHODS: A literature search was carried out using different search engines, like Sci-finder, Elsevier, ScienceDirect, RSC etc., for small molecules based on pyrrole and pyridine helpful in diagnosis and inducing apoptosis in cancer cells. The research findings on the application of these compounds from 2018-2023 were reviewed on a variety of cell lines, such as breast cancer, liver cancer, epithelial cancer, etc. Results: In this review, the published small molecules, pyrrole and pyridine and their derivatives, which have roles in the diagnosis and treatment of cancers, were discussed to provide some insight into the structural features responsible for diagnosis and treatment. The analogues with the chromeno-furo-pyridine skeleton showed the highest anticancer activity against breast cancer. The compound 5-amino-N-(1-(pyridin-4- yl)ethylidene)-1H-pyrazole-4-carbohydrazides was highly potent against HEPG2 cancer cell. Redaporfin is used for the treatment of cholangiocarcinoma, biliary tract cancer, cisplatin-resistant head and neck squamous cell carcinoma, and pigmentation melanoma, and it is in clinical trials for phase II. These structural features present a high potential for designing novel anticancer agents for diagnosis and drug development. CONCLUSION: Therefore, the N- and C-substituted pyrrole and pyridine-based novel privileged small Nheterocyclic scaffolds are potential molecules used in the diagnosis and treatment of cancer. This review discusses the reports on the synthesis of such molecules during 2018-2023. The review mainly discusses various diagnostic techniques for cancer, which employ pyrrole and pyridine heterocyclic scaffolds. Furthermore, the anticancer activity of N- and C-substituted pyrrole and pyridine-based scaffolds has been described, which works against different cancer cell lines, such as MCF-7, A549, A2780, HepG2, MDA-MB-231, K562, HT- 29, Caco-2 cells, Hela, Huh-7, WSU-DLCL2, HCT-116, HBL-100, H23, HCC827, SKOV3, etc. This review will help the researchers to obtain a critical insight into the structural aspects of pyrrole and pyridine-based scaffolds useful in cancer diagnosis as well as treatment and design pathways to develop novel drugs in the future.

The C1q and gC1qR axis as a novel checkpoint inhibitor in cancer.

Understanding at the molecular level of the cell biology of tumors has led to significant treatment advances in the past. Despite such advances however, development of therapy resistance and tumor recurrence are still unresolved major challenges. This therefore underscores the need to identify novel tumor targets and develop corresponding therapies to supplement existing biologic and cytotoxic approaches so that a deeper and more sustained treatment responses could be achieved. The complement system is emerging as a potential novel target for cancer therapy. Data accumulated to date show that complement proteins, and in particular C1q and its receptors cC1qR/CR and gC1qR/p33/HABP1, are overexpressed in most cancer cells and together are involved not only in shaping the inflammatory tumor microenvironment, but also in the regulation of angiogenesis, metastasis, and cell proliferation. In addition to the soluble form of C1q that is found in plasma, the C1q molecule is also found anchored on the cell membrane of monocytes, macrophages, dendritic cells, and cancer cells, via a 22aa long leader peptide found only in the A-chain. This orientation leaves its 6 globular heads exposed outwardly and thus available for high affinity binding to a wide range of molecular ligands that enhance tumor cell survival, migration, and proliferation. Similarly, the gC1qR molecule is not only overexpressed in most cancer types but is also released into the microenvironment where it has been shown to be associated with cancer cell proliferation and metastasis by activation of the complement and kinin systems. Co-culture of either T cells or cancer cells with purified C1q or anti-gC1qR has been shown to induce an anti-proliferative response. It is therefore postulated that in the tumor microenvironment, the interaction between C1q expressing cancer cells and gC1qR bearing cytotoxic T cells results in T cell suppression in a manner akin to the PD-L1 and PD-1 interaction.

Chasing Graphene-Based Anticancer Drugs: Where are We Now on the Biomedical Graphene Roadmap?

Graphene and graphene-based materials have attracted growing interest for potential applications in medicine because of their good biocompatibility, cargo capability and possible surface functionalizations. In parallel, prototypic graphene-based devices have been developed to diagnose, imaging and track tumor growth in cancer patients. There is a growing number of reports on the use of graphene and its functionalized derivatives in the design of innovative drugs delivery systems, photothermal and photodynamic cancer therapy, and as a platform to combine multiple therapies. The aim of this review is to introduce the latest scientific achievements in the field of innovative composite graphene materials as potentially applied in cancer therapy. The "Technology and Innovation Roadmap" published in the Graphene Flagship indicates, that the first anti-cancer drugs using graphene and graphene-derived materials will have appeared on the market by 2030. However, it is necessary to broaden understanding of graphene-based material interactions with cellular metabolism and signaling at the functional level, as well as toxicity. The main aspects of further research should elucidate how treatment methods (e.g., photothermal therapy, photodynamic therapy, combination therapy) and the physicochemical properties of graphene materials influence their ability to modulate autophagy and kill cancer cells. Interestingly, recent scientific reports also prove that graphene nanocomposites modulate cancer cell death by inducing precise autophagy dysfunctions caused by lysosome damage. It turns out as well that developing photothermal oncological treatments, it should be taken into account that near-infrared-II radiation (1000-1500 nm) is a better option than NIR-I (750-1000 nm) because it can penetrate deeper into tissues due to less scattering at longer wavelengths radiation.

Preliminary efficacy and safety of YSCH-01 in patients with advanced solid tumors: an investigator-initiated trial.

OBJECTIVE: To evaluate the safety and preliminary efficacy of YSCH-01 (Recombinant L-IFN adenovirus) in subjects with advanced solid tumors. METHODS: In this single-center, open-label, investigator-initiated trial of YSCH-01, 14 patients with advanced solid tumors were enrolled. The study consisted of two distinct phases: (1) the dose escalation phase and (2) the dose expansion phase; with three dose groups in the dose escalation phase based on dose levels (5.0×109 viral particles (VP)/subject, 5.0×1010 VP/subject, and 5.0×1011 VP/subject). Subjects were administered YSCH-01 injection via intratumoral injections. The safety was assessed using National Cancer Institute Common Terminology Criteria for Adverse Events V.5.0, and the efficacy evaluation was performed using Response Evaluation Criteria in Solid Tumor V.1.1. RESULTS: 14 subjects were enrolled in the study, including 9 subjects in the dose escalation phase and 5 subjects in the dose expansion phase. Of the 13 subjects included in the full analysis set, 4 (30.8%) were men and 9 (69.2%) were women. The most common tumor type was lung cancer (38.5%, 5 subjects), followed by breast cancer (23.1%, 3 subjects) and melanoma (23.1%, 3 subjects). During the dose escalation phase, no subject experienced dose-limiting toxicities. The content of recombinant L-IFN adenovirus genome and recombinant L-IFN protein in blood showed no trend of significant intergroup changes. No significant change was observed in interleukin-6 and interferon-gamma. For 11 subjects evaluated for efficacy, the overall response rate with its 95% CI was 27.3% (6.02% to 60.97%) and the disease control rate with its 95% CI was 81.8% (48.22% to 97.72%). The median progression-free survival was 4.97 months, and the median overall survival was 8.62 months. In addition, a tendency of decrease in the sum of the diameters of target lesions was observed. For 13 subjects evaluated for safety, the overall incidence of adverse events (AEs) was 92.3%, the overall incidence of adverse drug reactions (ADRs) was 84.6%, and the overall incidence of >Grade 3 AEs was 7.7%, while no AEs/ADRs leading to death occurred. The most common AEs were fever (69.2%), nausea (30.8%), vomiting (30.8%), and hypophagia (23.1%). CONCLUSIONS: The study shows that YSCH-01 injections were safe and well tolerated and exhibited preliminary efficacy in patients with advanced solid tumors, supporting further investigation to evaluate its efficacy and safety. TRIAL REGISTRATION NUMBER: NCT05180851.

Ultrasmall Fe3O4 nanoparticles self-assembly induced dual-mode T1/T2-weighted magnetic resonance imaging and enhanced tumor synergetic theranostics.

Individual theranostic agents with dual-mode MRI responses and therapeutic efficacy have attracted extensive interest due to the real-time monitor and high effective treatment, which endow the providential treatment and avoid the repeated medication with side effects. However, it is difficult to achieve the integrated strategy of MRI and therapeutic drug due to complicated synthesis route, low efficiency and potential biosafety issues. In this study, novel self-assembled ultrasmall Fe3O4 nanoclusters were developed for tumor-targeted dual-mode T1/T2-weighted magnetic resonance imaging (MRI) guided synergetic chemodynamic therapy (CDT) and chemotherapy. The self-assembled ultrasmall Fe3O4 nanoclusters synthesized by facilely modifying ultrasmall Fe3O4 nanoparticles with 2,3-dimercaptosuccinic acid (DMSA) molecule possess long-term stability and mass production ability. The proposed ultrasmall Fe3O4 nanoclusters shows excellent dual-mode T1 and T2 MRI capacities as well as favorable CDT ability due to the appropriate size effect and the abundant Fe ion on the surface of ultrasmall Fe3O4 nanoclusters. After conjugation with the tumor targeting ligand Arg-Gly-Asp (RGD) and chemotherapy drug doxorubicin (Dox), the functionalized Fe3O4 nanoclusters achieve enhanced tumor accumulation and retention effects and synergetic CDT and chemotherapy function, which serve as a powerful integrated theranostic platform for cancer treatment.

Ceria nanoparticles: biomedical applications and toxicity. / 二氧化铈纳米颗粒：生物医学应用和毒性.

Ceria nanoparticles (CeO2 NPs) have become popular materials in biomedical and industrial fields due to their potential applications in anti-oxidation, cancer therapy, photocatalytic degradation of pollutants, sensors, etc. Many methods, including gas phase, solid phase, liquid phase, and the newly proposed green synthesis method, have been reported for the synthesis of CeO2 NPs. Due to the wide application of CeO2 NPs, concerns about their adverse impacts on human health have been raised. This review covers recent studies on the biomedical applications of CeO2 NPs, including their use in the treatment of various diseases (e.|g., Alzheimer's disease, ischemic stroke, retinal damage, chronic inflammation, and cancer). CeO2 NP toxicity is discussed in terms of the different systems of the human body (e.|g., cytotoxicity, genotoxicity, respiratory toxicity, neurotoxicity, and hepatotoxicity). This comprehensive review covers both fundamental discoveries and exploratory progress in CeO2 NP research that may lead to practical developments in the future.

The STING agonist IMSA101 enhances chimeric antigen receptor T cell function by inducing IL-18 secretion.

As a strategy to improve the therapeutic success of chimeric antigen receptor T cells (CART) directed against solid tumors, we here test the combinatorial use of CART and IMSA101, a newly developed stimulator of interferon genes (STING) agonist. In two syngeneic tumor models, improved overall survival is observed when mice are treated with intratumorally administered IMSA101 in addition to intravenous CART infusion. Transcriptomic analyses of CART isolated from tumors show elevated T cell activation, as well as upregulated cytokine pathway signatures, in particular IL-18, in the combination treatment group. Also, higher levels of IL-18 in serum and tumor are detected with IMSA101 treatment. Consistent with this, the use of IL-18 receptor negative CART impair anti-tumor responses in mice receiving combination treatment. In summary, we find that IMSA101 enhances CART function which is facilitated through STING agonist-induced IL-18 secretion.

Chemotherapy-induced PTEN-L secretion promotes the selection of PTEN-deficient tumor cells.

BACKGROUND: PTEN loss has been identified in various tumor types and is linked to unfavorable clinical outcomes. In addition to PTEN mutation, multiple mechanisms contribute to PTEN loss during tumor development. However, the natural selection process of PTEN-deficient tumor cells remains unclear. Here, we aimed at further elucidating the role of PTEN-L in tumor progression. METHODS: PTEN knockout cell lines were generated using CRISPR/Cas9 technology. Ni-NTA affinity column chromatography was employed for PTEN-L purification. Tumor cell metastasis was evaluated in murine models and observed using the IVIS Spectrum Imaging System. RNA-sequencing, western blotting, PCR, flow cytometry, and cell proliferation assays were employed to investigate tumor cell dormancy and related mechanisms. RESULTS: The chemotherapeutic drugs, cisplatin, paclitaxel, and doxorubicin, induced tumor cells to secrete PTEN-long (PTEN-L), which shields PTEN-deficient tumor cells from chemotherapy-induced apoptosis better than it shields PTEN-intact cells. Further investigation revealed that PTEN-L treatment induced dormancy in PTEN-null tumor cells, characterized by an increase in p16 and p27 levels, cell-cycle arrest, reduced cell proliferation, and enhanced DNA repair. Furthermore, PTEN-L treatment selectively promoted the accumulation and growth of PTEN-null tumor cells in the lungs of C57BL/6J mice, while evading immune surveillance. Mechanistically, PTEN-L induced dormancy in PTEN-null tumor cells by activating the p38 signaling pathway. Addition of a p38 inhibitor effectively reversed dormancy and growth of PTEN-deficient tumor cells in the lungs. We also demonstrated that PTEN expression played a pivotal role in determining the outcome of PTEN-L-mediated antitumor therapy. CONCLUSIONS: In summary, PTEN-L was identified as a potent inducer of dormancy in PTEN-deficient tumor cells, which increased their efficient selection within the tumor microenvironment.

Connective Tissue Growth Factor: Regulation, Diseases, and Drug Discovery.

In drug discovery, selecting targeted molecules is crucial as the target could directly affect drug efficacy and the treatment outcomes. As a member of the CCN family, CTGF (also known as CCN2) is an essential regulator in the progression of various diseases, including fibrosis, cancer, neurological disorders, and eye diseases. Understanding the regulatory mechanisms of CTGF in different diseases may contribute to the discovery of novel drug candidates. Summarizing the CTGF-targeting and -inhibitory drugs is also beneficial for the analysis of the efficacy, applications, and limitations of these drugs in different disease models. Therefore, we reviewed the CTGF structure, the regulatory mechanisms in various diseases, and drug development in order to provide more references for future drug discovery.

Berberine Improves Cancer-Derived Myocardial Impairment in Experimental Cachexia Models by Targeting High-Mobility Group Box-1.

Cardiac disorders in cancer patients pose significant challenges to disease prognosis. While it has been established that these disorders are linked to cancer cells, the precise underlying mechanisms remain elusive. In this study, we investigated the impact of cancerous ascites from the rat colonic carcinoma cell line RCN9 on H9c2 cardiomyoblast cells. We found that the ascites reduced mitochondrial volume, increased oxidative stress, and decreased membrane potential in the cardiomyoblast cells, leading to apoptosis and autophagy. Although the ascites fluid contained a substantial amount of high-mobility group box-1 (HMGB1), we observed that neutralizing HMGB1 with a specific antibody mitigated the damage inflicted on myocardial cells. Our mechanistic investigations revealed that HMGB1 activated both nuclear factor κB and phosphoinositide 3-kinases-AKT signals through HMGB1 receptors, namely the receptor for advanced glycation end products and toll-like receptor-4, thereby promoting apoptosis and autophagy. In contrast, treatment with berberine (BBR) induced the expression of miR-181c-5p and miR-340-5p while suppressing HMGB1 expression in RCN9 cells. Furthermore, BBR reduced HMGB1 receptor expression in cardiomyocytes, consequently mitigating HMGB1-induced damage. We validated the myocardial protective effects of BBR in a cachectic rat model. These findings underscore the strong association between HMGB1 and cancer cachexia, highlighting BBR as a promising therapeutic agent for myocardial protection through HMGB1 suppression and modulation of the signaling system.

Macrophage Migration Inhibitory Factor (MIF) and D-Dopachrome Tautomerase (DDT): Pathways to Tumorigenesis and Therapeutic Opportunities.

Discovered as inflammatory cytokines, MIF and DDT exhibit widespread expression and have emerged as critical mediators in the response to infection, inflammation, and more recently, in cancer. In this comprehensive review, we provide details on their structures, binding partners, regulatory mechanisms, and roles in cancer. We also elaborate on their significant impact in driving tumorigenesis across various cancer types, supported by extensive in vitro, in vivo, bioinformatic, and clinical studies. To date, only a limited number of clinical trials have explored MIF as a therapeutic target in cancer patients, and DDT has not been evaluated. The ongoing pursuit of optimal strategies for targeting MIF and DDT highlights their potential as promising antitumor candidates. Dual inhibition of MIF and DDT may allow for the most effective suppression of canonical and non-canonical signaling pathways, warranting further investigations and clinical exploration.

Structure-property modeling of coumarins and coumarin-related compounds in pharmacotherapy of cancer by employing graphical topological indices.

Coumarins, a subgroup of colorless and crystalline oxygenated heterocyclic compounds originally discovered in the plant Dipteryx odorata, were the subject of a recent study investigating their quantitative structure-activity relationship (QSAR) in cancer pharmacotherapy. This study utilized graph theoretical molecular descriptors, also known as topological indices, as a numerical representation method for the chemical structures embedded in molecular graphs. These descriptors, derived from molecular graphs, play a pivotal role in quantitative structure-property relationship (QSPR) analysis. In this paper, intercorrelation between the Balban index, connective eccentric index, eccentricity connectivity index, harmonic index, hyper Zagreb index, first path Zagreb index, second path Zagreb index, Randic index, sum connectivity index, graph energy and Laplacian energy is studied on the set of molecular graphs of coumarins. It is found that the pairs of degree-based indices are highly intercorrelated. The use of these molecular descriptors in structure-boiling point modeling was analyzed. Finally, the curve-linear regression between considered molecular descriptors with physicochemical properties of coumarins and coumarin-related compounds is obtained.